Sr. Data Scientist (Global Media Agency) at Global Media Agency - A client of Merito · Gurugram, Bengaluru (Bangalore), Mumbai · 4 - 9 years · Posted 11 Apr 2022
Sr. Data Scientist (Global Media Agency)
at Global Media Agency - A client of Merito
Our client combines Adtech and Martech platform strategy with data science & data engineering expertise, helping our clients make advertising work better for people.
- Act as primary day-to-day contact on analytics to agency-client leads
- Develop bespoke analytics proposals for presentation to agencies & clients, for delivery within the teams
- Ensure delivery of projects and services across the analytics team meets our stakeholder requirements (time, quality, cost)
- Hands on platforms to perform data pre-processing that involves data transformation as well as data cleaning
- Ensure data quality and integrity
- Interpret and analyse data problems
- Build analytic systems and predictive models
- Increasing the performance and accuracy of machine learning algorithms through fine-tuning and further
- Visualize data and create reports
- Experiment with new models and techniques
- Align data projects with organizational goals
Requirements
- Min 6 - 7 years’ experience working in Data Science
- Prior experience as a Data Scientist within a digital media is desirable
- Solid understanding of machine learning
- A degree in a quantitative field (e.g. economics, computer science, mathematics, statistics, engineering, physics, etc.)
- Experience with SQL/ Big Query/GMP tech stack / Clean rooms such as ADH
- A knack for statistical analysis and predictive modelling
- Good knowledge of R, Python
- Experience with SQL, MYSQL, PostgreSQL databases
- Knowledge of data management and visualization techniques
- Hands-on experience on BI/Visual Analytics Tools like PowerBI or Tableau or Data Studio
- Evidence of technical comfort and good understanding of internet functionality desirable
- Analytical pedigree - evidence of having approached problems from a mathematical perspective and working through to a solution in a logical way
- Proactive and results-oriented
- A positive, can-do attitude with a thirst to continually learn new things
- An ability to work independently and collaboratively with a wide range of teams
- Excellent communication skills, both written and oral

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Job Summary:
We are looking for a skilled Data Scientist with strong expertise in demand forecasting, predictive analytics, and emerging Generative AI technologies. The ideal candidate should have hands-on experience in machine learning, deep learning, NLP, and LLM-based solutions, along with proficiency in Python, SQL, Power BI, and advanced Excel. This role involves building scalable forecasting models and leveraging AI/GenAI to deliver actionable business insights.
Key Responsibilities:
- Develop and deploy demand forecasting models using machine learning and deep learning techniques.
- Analyze historical data to identify trends, seasonality, and demand patterns.
- Build predictive models to improve supply chain and inventory planning.
- Work with large datasets using Python and SQL for data extraction, transformation, and analysis.
- Design dashboards and reports using Power BI for business stakeholders.
- Utilize advanced Excel techniques (Pivot Tables, Power Query, formulas) for analysis and reporting.
- Build and integrate NLP-based solutions for text data analysis and insights.
- Develop and implement LLM-based applications using Generative AI frameworks.
- Design and deploy RAG (Retrieval-Augmented Generation) pipelines for intelligent data retrieval and response generation.
- Collaborate with cross-functional teams (operations, finance, product) to align forecasting and AI solutions.
- Continuously improve model accuracy and performance through experimentation and optimization.
Required Skills:
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
- Solid understanding of machine learning & deep learning algorithms.
- Experience in demand forecasting / time-series analysis (ARIMA, Prophet, LSTM, etc.).
- Hands-on experience with NLP techniques and libraries (NLTK, SpaCy, Transformers).
- Experience working with LLMs and Generative AI frameworks (OpenAI, Hugging Face, LangChain, etc.).
- Strong understanding of RAG architectures and vector databases (FAISS, Pinecone, etc.).
- Advanced knowledge of SQL for data manipulation.
- Hands-on experience with Power BI for visualization and reporting.
- Expertise in advanced Excel (Power Query, dashboards, data modeling).
- Strong analytical and problem-solving skills.
Preferred Qualifications:
- Experience in supply chain, logistics, or e-commerce forecasting.
- Knowledge of cloud platforms (AWS, Azure, or GCP).
- Familiarity with data pipelines and ETL processes.
- Understanding of business metrics and KPIs related to demand planning.
Job Description:
As a Data Science Intern, you will collaborate with our data science and analytics teams to work on meaningful projects involving data analysis, predictive modeling, and statistical modeling. You will have the opportunity to apply your academic knowledge in a practical, fast-paced environment, contribute to key data-driven projects, and gain valuable experience with industry-leading tools and technologies.
Responsibilities:
- Assist in collecting, cleaning, and preprocessing data from various sources.
- Perform exploratory data analysis to identify trends, patterns, and anomalies.
- Develop and implement machine learning models and algorithms.
- Create data visualizations and reports to communicate findings to stakeholders.
- Collaborate with team members on data-driven projects and research.
- Participate in meetings and contribute to discussions on project progress and strategy.
- Work with large datasets to clean, preprocess, and analyze data.
- Build and deploy statistical and machine learning models to generate actionable insights.
- Conduct exploratory data analysis (EDA) to uncover trends, patterns, and correlations.
- Assist in the creation of data visualizations and dashboards for reporting insights.
- Support the development and improvement of data pipelines and algorithms.
- Collaborate with cross-functional teams to understand data needs and translate them into actionable analytics solutions.
- Contribute to the documentation and presentation of results, findings, and recommendations.
- Participate in team meetings, brainstorming sessions, and project discussions.
Duration: 03 Months (with the possibility of extending up to 6 months)
MODE: Work From Home (Online)
Requirements:
- Any Graduate / PassOuts / Freasher can apply.
- Currently pursuing a Bachelor's or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
- Proficiency in programming languages such as Python, R, or SQL.
- Strong foundation in statistics, probability, and data analysis techniques.
Benefits
Internship Certificate
Letter of recommendation
Stipend Performance Based
Part time work from home (2-3 Hrs per day)
5 days a week, Fully Flexible Shift
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Sr.Data Scientist,Python, AI ML
We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.
Title : Marketing Analytics Specialist
Experience : 5 to 8 yrs
Location : Anywhere in India – Preferred Chennai
Type of Hire : PwD/Non PwD
Work type : Remote
Employment Type : Full Time
Notice Period : Immediate
Workday : Mon to Fri
Role Overview
We are looking for an experienced Marketing Analytics Specialist to derive actionable commercial insights from Reckitt’s cross-channel e-commerce sales data. The role involves integrating data from multiple, inconsistently structured sources, developing scalable data pipelines and data models, creating business intelligence dashboards, and analyzing the impact of media platform spending on sales performance across various retailer platforms.
Key Responsibilities
- Commercial Analytics: Analyze cross-channel e-commerce sales data to identify trends, performance drivers, and actionable commercial insights.
- Business Requirements: Collaborate with business stakeholders to understand reporting requirements and translate them into analytical solutions.
- Data Architecture: Design and implement efficient data storage, retrieval, and processing architectures.
- ETL Development: Build and maintain robust, scalable ETL pipelines to integrate data from multiple source systems into data warehouses or other storage solutions.
- Data Modelling: Develop and maintain data models aligned with business reporting and analytical requirements.
- Data Quality: Implement data quality checks, validation, and reconciliation processes to ensure data accuracy, completeness, and consistency.
- BI Dashboards & Reporting: Design and develop interactive dashboards and reports that communicate business performance and insights effectively.
- Media Spend Analysis: Analyze the impact of media platform spending on sales performance across multiple retailer platforms and identify opportunities to improve marketing effectiveness.
- End-User Training: Provide training, documentation, and ongoing support to enable business users to use BI tools effectively.
Required Skills
- 5+ years of experience in Marketing Analytics, Data Analytics, Business Intelligence, or a related field.
- Prior hands-on experience in Marketing Analytics, with full proficiency in Claude AI
- Strong SQL skills for data extraction, transformation, and analysis.
- Hands-on experience with ETL/ELT pipelines and data integration from multiple sources.
- Experience with data warehousing concepts and data modeling.
- Proficiency in Power BI, Tableau, or other BI visualization tools.
- Experience analyzing e-commerce sales, marketing performance, media spending, or retailer data.
- Knowledge of data quality, data validation, and reconciliation techniques.
- Strong analytical, problem-solving, and stakeholder communication skills.
Good to Have
- Experience in FMCG, retail, consumer goods, or e-commerce analytics.
- Understanding of digital marketing metrics such as ROI, ROAS, and campaign performance.
- Exposure to marketing attribution or Marketing Mix Modeling (MMM).
- Experience with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Azure Synapse.
- Knowledge of Python or data transformation tools such as dbt.
Role Overview
As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact.
Key Responsibilities
Data Science & Machine Learning
- Analyze structured and unstructured data to identify patterns, trends, and business opportunities.
- Perform exploratory data analysis (EDA), feature engineering, and data preparation.
- Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.
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- Design and execute experiments to improve model accuracy and business outcomes.
AI Solution Development
- Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.
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- Contribute to Generative AI and advanced analytics initiatives where applicable.
- Document methodologies, model performance, and key findings.
Required Technical Skills
- Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.
- Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.
- Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.
- Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.
- Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.
- Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.
- Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.
- Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.
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- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.
- 2–4 years of experience developing machine learning or data science solutions.
- Experience working on end-to-end data science projects in a business environment.
Nice to Have
- Exposure to Generative AI, LLMs, RAG, or Agentic AI.
- Experience with Computer Vision or Natural Language Processing (NLP).
- Familiarity with cloud-based AI platforms.
- Knowledge of construction, engineering, manufacturing, or industrial domains.
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Soft Skills
Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.
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Exp : 4 - 12 yrs
Edu : BE/B.tech/MCA
Work Location : Pune
Notice Period : Immediate - 15 days
Skills :
4+ years of experience in data engineering, data science, or related domains.
Hands-on experience with SQL, Python, and distributed data systems.
Knowledge of machine learning techniques and statistical analysis.
Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
Familiarity with DevOps practices and CI/CD for data pipelines.
Platforms & Operations Experience (Preferred)
- Experience working with Azure, AWS, or Google Cloud data tools.
Operational experience with data orchestration tools (Airflow, ADF, Glue).
Understanding of Kubernetes, Docker, or containerized environments.
Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).
Experience in monitoring, logging, and alerting operations for data workflows.
We are looking for a hands-on Lead Data Scientist with strong analytical, machine learning, and problem-solving skills to work in a client-facing environment.
The role requires someone who can independently identify opportunities, formulate hypotheses, design solutions, and drive initiatives from analysis through experimentation and production implementation. The candidate should also be comfortable guiding team members and working closely with engineering and client stakeholders.
Responsibilities:
- Analyse complex datasets to identify patterns, issues, and opportunities.
- Formulate and validate hypotheses through structured analysis and experimentation.
- Build and improve machine learning and anomaly detection solutions.
- Design end-to-end solutions considering data, modelling, engineering, and production constraints.
- Perform root cause analysis across models, data, and systems.
- Work with engineering teams on feature pipelines, model inference, and production deployment.
- Lead technical discussions with clients and communicate recommendations, trade-offs, and expected impact.
- Guide team members on analysis, modelling, and solution design.
- Proactively identify initiatives and roadmap items that can add value to the project.
Requirements:
- Strong foundation in statistics and machine learning.
- Strong hands-on experience with Python and SQL.
- Hands-on experience with Python ML and data frameworks such as Pandas, NumPy, scikit-learn, TensorFlow/Keras, Dask, Matplotlib, Boto3 SageMaker Python SDK, and Horovod.
- Strong data analysis, hypothesis-generation, and problem-solving skills.
- Experience with standard supervised and unsupervised ML techniques.
- Experience with anomaly detection techniques such as Isolation Forest and Autoencoders.
- Experience building and deploying production ML solutions.
- Working knowledge of data engineering and real-time / batch inference environments.
- Strong communication and stakeholder-management skills.
- Ability to lead technical work and guide cross-functional teams.
Good to Have:
- Experience in fraud detection or risk modelling.
- Experience with Graph Neural Networks.
- Exposure to real-time systems, streaming features, and low-latency data stores.
- Experience in AdTech, e-commerce, gaming, mobile applications, or similar high-volume consumer platforms.
About the Company:
WebMD Health Corp., an Internet Brands Company, is the leading provider of health information services, serving patients, physicians, health care professionals, employers, and health plans through our public and private online portals, mobile platforms, and health-focused publications. The WebMD Health Network includes WebMD Health, Medscape, Jobson Healthcare Information, prIME Oncology, MediQuality, Frontline, QxMD, Vitals Consumer Services, MedicineNet, eMedicineHealth, RxList, OnHealth, Medscape Education, and other owned WebMD sites. WebMD®, Medscape®, CME Circle®, Medpulse®, eMedicine®, MedicineNet®, theheart.org®, and RxList® are among the trademarks of WebMD Health Corp. or its subsidiaries. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
For Company details, visit our website: www.webmd.com
Experience: 3+ years
Qualification: Master's degree in Computer Science, Statistics, Mathematics, or a related field.
Work Timings: 2 PM to 11 PM IST
Position Requirement:
- Write clean and efficient code in Python and/or R for data analysis, statistical modeling, and machine learning tasks.
- Apply statistical and machine learning techniques to analyze large datasets and extract meaningful patterns, trends, and insights. Develop and implement predictive models for various business applications.
- Formulate hypothesis tests and design experiments to validate assumptions, measure the impact of changes, and optimize decision-making processes.
- Demonstrate strong SQL skills for efficient data querying and manipulation using window functions.
- Work with large datasets and ensure data quality and accuracy.
- Experience with dashboarding tools like Tableau is a plus to visualize and present data-driven insights to both technical and non-technical stakeholders.
- Ability to communicate complex technical concepts and insights in a clear and concise manner to both technical and non-technical audiences. Engage with the leadership team and clients to understand business requirements and provide data-driven solutions.
- Work with real world case studies in Data Science and a chance to implement various modelling techniques. Opportunity to independently execute and lead analytical projects and assignments.
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Technical Skills needed:
1.Experience with data manipulation in SQL environment is a must. Experience with BigQuery/Vertica data warehousing is good to have
- Experience with statistical and data manipulation tools such as Python or R is a must
- Need very good expertise in using Microsoft Excel, and Microsoft PowerPoint. Excellent presentation skills required
- Experience developing statistical models like hypothesis testing, regression models, classifications models, forecasting etc is a must
- Algorithm designing and implementation skills in R or Python is required
Requirements
- B.Tech/B.E. / MSc Statistics from premier institutes with
- Minimum 80% marks in 10th and 12th
- Minimum 75% marks in graduation
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- Proven experience in data science, statistical modeling, and machine learning applications.
- Strong proficiency in Python and/or R programming languages.
- Solid understanding of statistical concepts, hypothesis testing, and experimental design
- Expertise in SQL for data querying and manipulation.
- Familiarity with dashboarding tools is a plus.
- Excellent presentation, communication and interpersonal skills.
About Us
Corporate Web Solutions works on technology-driven digital solutions involving data, automation, web technologies, and artificial intelligence. Our internship programs focus on practical learning and real-world project exposure.
Role Overview
As a Data Science Intern, you'll work with datasets to perform analysis, visualization, and machine learning tasks while learning modern AI-assisted workflows.
Key Responsibilities
- Collect, clean, and analyze datasets.
- Perform exploratory data analysis.
- Create data visualizations and reports.
- Assist in developing machine learning models.
- Work with Python-based data science tools.
- Explore AI tools for data analysis and productivity.
Requirements
- Basic knowledge of Python.
- Understanding of data analysis fundamentals.
- Familiarity with Pandas and NumPy is a plus.
- Basic understanding of statistics.
- Analytical and problem-solving skills.
Perks
- Certificate of Internship
- Flexible work hours
- Mentorship and real project exposure
- Potential for PPO
- Letter of Recommendation
- Performance-Based Stipend available up to ₹18,000/month
Key Responsibilities
Strong understanding of Machine Learning algorithms (supervised and unsupervised)
Hands-on experience with Deep Learning frameworks (TensorFlow, PyTorch, or similar)
Experience in NLP techniques and libraries (NLTK, spaCy, Hugging Face, etc.)
Solid knowledge of Statistics, probability, and data analysis methods
Proficiency in SQL for querying relational databases
Strong programming skills in Python (or similar languages)
Excellent communication skills with the ability to explain complex concepts simply
Required Qualifications
3+ years of hands-on experience as a Data Scientist or in a similar role.
Strong expertise in classical machine learning and regression modeling.
Solid understanding of statistics, including probability, distributions, hypothesis testing,
and correlation analysis.
Proficiency in Python with libraries such as: scikit-learn pandas NumPy
Experience working with structured/tabular data.
Strong problem-solving and analytical thinking skills.
Ability to clearly explain models and results to non-technical stakeholders.













